Quantica Capital AG

Bruno Gmür has an impressive professional and academic background in finance. It is a background associated with the type of financial academics that often like to look down at the world of managed futures, especially those applying a trend following approach.


So it is a little surprising that Gmür would go on to launch successful long-term trend following commodity trading advisor Quantica Capital, using a strategy that defies the Efficient Market Hypothesis (EMH), which holds that assets prices fully reflect all available information.

Gmür holds a Ph.D. in financial economics from the University of Zurich and a master’s degree in mathematics from the Swiss Federal Institute of Technology. After a stint teaching graduate-level courses at the University of Zurich, Gmür held positions at Swiss Re in financial reinsurance structuring and at Bank Julius Baer, where he was head of the quantitative team and a voting member of the bank’s strategic asset allocation committee.

With this background Gmür was a solid adherent to the EMH.

“I had no background in trading. My background was in academics, I was teaching econometrics, game theory and all kinds of quantitatively related stuff [on] financial markets,” Gmür says.

“By doing that I was a proponent and believer in the Efficient Market Hypothesis.”

But once Gmür performed deeper research into applied quantitative asset allocation, he experienced a conversion of sorts. “I found that signals related to trend following had the best predictive power for financial market development over a medium- to long-term investment horizon,” he says.

Applying those signals and improving on the trend following method would become his life’s work.

In 2003 Gmür founded Quantica Capital and in 2005 launched his Quantica Managed Futures strategy trading a $100 million allocation from a large global macro hedge fund. “They were interested in our systematic approach to diversify their more discretionary global macro allocation,” Gmür says. His program trades approximately 80 liquid markets including equity index futures, fixed income futures, commodity futures and FX futures.

Gmür didn’t abandon adherence to a trusted financial principle just to launch a basic trend following strategy, he was determined to offer something unique.

“We are offering a very highly stylized mediumto long-term trend following program,” Gmür says. “Our correlation to the trend following space is quite high; however, we have managed to outperform our peers and the [sector] indexes over the last 14 years by 4% per annum.”

He attributes Quantica’s outperformance to getting into trends early and better risk management.

“Our approach to trend following is more risk based than traditional trend following. Trends are not only measured in terms of price momentum, but in terms of risk adjusted price momentum,” he says. “We always measure the price movement in relation to the risk. The other [component], which is probably more important, is that our trend identification does not act on individual markets alone but analyzes relative risk adjusted momentum.”

Gmür calls this a generalized cross-sectional momentum approach. The strategy looks at trends in relation to all the other markets it trades in their portfolio. “Our trends are always identified on a relative approach. When we analyze an equity market we look at the risk-adjusted performance of the equity market not only in relation to price but also in terms of relative outperformance against other equity markets, but also against treasuries or gold or commodities.”

Gmür is able to detect a divergence from other markets, which indicates the development of a relative trend at an earlier stage than if he simply looked at one market’s price momentum. “The market does not really need to go up to [generate a signal], it just needs a level of outperformance versus other markets,” he says.

His approach takes the whole correlation structure of the market into account. “Our trend identification is different [from a] traditional trend following systems in the sense that markets are not analyzed in an isolated way. The signal generation universe has a much higher dimension,” he says.

Quantica does not directly trade spreads, but their trend signals are identified based on analyzing spreads. “We are trading 80 markets, so we are analyzing 80 markets x 79 spreads. For each market we analyze 79 spreads. This increases robustness and stability of the model in an exponential way.”

While Quantica has outperformed the trend following space consistently over the last 14 years, that outperformance spiked—20% over the last three years—during the recent poor performance period for trend followers. Gmür attributes this to their risk-based approach and his ability to exploit the movement in equity indexes.

The last two years (prior to October 2018), equity volatility was low despite the uptrend. So our approach of detecting risk adjusted trends has resulted in much stronger signals in equity markets and could be deployed in equity trends much earlier and stronger than our peers,” Gmür says. “We were able to extract trend following premium in periods when volatility is low or decreasing.”

This was highlighted in 2016 when the markets moved from a risk-off to a risk-on environment. Gmür describes the first half of 2016 as characterized by fear and weak equity markets peaking with the Brexit vote. That began to reverse in the second half, which Quanticas’s model exploited. “On a relative basis our models identified outperformance of risk-on assets (equities) versus risk-off assets (Treasuries, yen) and increased equity allocation quite quickly. When the risk-off regime changed to risk-on, our program was already adjusting risk from bonds into equities. That transition happened much quicker than more traditional CTAs and explains much of our outperformance.”

“Investors are focused too much on pure signal generation and underestimate the importance of risk management, portfolio construction and implementation.”

Gmür says that a complete investment process includes signal generation, portfolio construction, risk management and implementation; and all aspects of that process can add value. “Investors are focused too much on pure signal generation and underestimate the importance of risk management, portfolio construction and implementation,” he says. “The reason why trend following returns are highly correlated is that signal generation [is similar], but performance can deviate a lot among trend followers. The reason is mostly portfolio construction, risk management and implementation.”

“The Efficient Market Hypothesis is a model of reality, and in reality things are slightly different. A model is just a model, not reality.”

Gmür believes it is this correlation that has led to the growth of various alternative risk premium products that try to access trend following beta.

“Some Investors believe trend following is very easy to do and can access trend following returns through cheap passive products,” Gmür says. “The truth is they can get the correlation right because trend following signals are highly correlated, but they will not get the returns because the cheap products completely ignore the process of portfolio construction, risk management and implementation.”

He says that managers can improve performance by as much as 2% in each of those processes. He attributes Quantica’s ability to outperform peers to perfecting these processes along with their relative and risk based approach.

Gmür says he is still an admirer of the EMH, but adds, “The Efficient Market Hypothesis is a model of reality and in reality things are slightly different. A model is just a model, not reality.”

While his research convinced him that trend following signals worked, he sees that as adding to his previous research. “If you take everything that is good in the model and expand it to incorporate certain things that are not captured in the model, it doesn’t say it is right or wrong,” Gmür says. “I converted, but took with me all the theoretical knowledge about market efficiencies, about statistics, risk theory and combined that and applied the statistical evidence of trend following to what I believe is a very efficient system.”

With that Gmür has gone about building a better trend following trap and believes investors need to access this source of alpha. “The biggest conceptual benefit of trend following is crisis alpha. If you look back in history you can see that for every era there is a crisis and a correction of 30% in the equity markets every 10 years or so,” he says. “Long only or 60-40 investors are not prepared for this correction. It will happen. There will be a next crisis, we don’t know when but we have high confidence that trend followers are prepared for the crisis.”

And Gmür is confident his risk-based models along with superior portfolio construction, risk management and implementation will capture more of those trends.